Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels

Details Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels

2011-05-27

arxiv.org/abs/1105.5542v1

Computer Science

Information Theory

Scientific paper

The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source\channel models. The focus of the paper is on binary-input channels with constraints on the allowed input configurations. The problems of numerically computing the information rate, and even the noiseless capacity, of such channels has so far remained largely unsolved. Both problems can be reduced to computing a Monte Carlo estimate of a partition function. The proposed algorithms use tree-based Gibbs sampling and multilayer (multitemperature) importance sampling. The viability of the proposed algorithms is demonstrated by simulation results.

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